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@ARTICLE{adler1997,
  author = {Adler, A. and Amyot, R. and Guardo, R. and Bates, J. H. T. and Berthiaume,
	Y.},
  title = {Monitoring changes in lung air and liquid volumes with electrical
	impedance tomography},
  journal = {Journal of Applied Physiology},
  year = {1997},
  volume = {83},
  pages = {1762-1767},
  number = {5}
}

@ARTICLE{adler2006,
  author = {Adler, A. and Lionheart, W. R. B.},
  title = {Uses and abuses of EIDORS: an extensible software base for EIT},
  journal = {Physiological Measurement},
  year = {2006},
  volume = {27},
  pages = {S25-S42},
  number = {5}
}

@BOOK{lapackman,
  title = {LAPACK's user's guide},
  publisher = {Society for Industrial and Applied Mathematics},
  year = {1992},
  author = {Anderson, E. and Bai, Z. and Bischof, C. and Demmel, J. and Dongarra,
	J. and Du Croz, J. and Greenbaum, A. and Hammarling, S. and McKenney,
	A. and Ostrouchov, S. and Sorensen, D.},
  address = {Philadelphia, PA, USA},
  isbn = {0-89871-294-7}
}

@ARTICLE{balleza2007,
  author = {Balleza, M. and Fornos, J. and Calaf, N. and Feixas, T. and Gonzalez,
	M. and Anton, D. and Riu, P. and Casan, P.},
  title = {Monitoring of breathing pattern at rest by electrical impedance tomography},
  journal = {Archivos De Bronconeumologia},
  year = {2007},
  volume = {43},
  pages = {300-303},
  number = {6}
}

@ARTICLE{barber1984,
  author = {Barber, D. C. and Brown, B. H.},
  title = {Applied potential tomography},
  journal = {Journal of Physics E-Scientific Instruments},
  year = {1984},
  volume = {17},
  pages = {723-733},
  number = {9}
}

@ARTICLE{bayford2006,
  author = {Bayford, R. H.},
  title = {Bioimpedance tomography (Electrical impedance tomography)},
  journal = {Annual Review of Biomedical Engineering},
  year = {2006},
  volume = {8},
  pages = {63-91},
  abstract = {Electrical impedance tomography (EIT) is a relatively new imaging
	method that has evolved over the past 20 years. It has the potential
	to be of great value in clinical diagnosis; however, EIT is a technically
	difficult problem to solve in terms of developing hardware for data
	capture and the algorithms to reconstruct the images. This review
	looks at the development of EIT and how it has evolved. It focuses
	on its clinical applications, examining hardware for the collection
	of data and reconstruction algorithms to generate images. Finally,
	this review looks at future developments that are evolving from FIT
	These new variations use mixed modalities that may produce interesting
	new clinical imaging tools.},
  keywords = {electrical impedance spectroscopy; imaging; hardware systems; reconstruction
	algorithms EIT IMAGE-RECONSTRUCTION; HUMAN BRAIN-FUNCTION; SEMIANALYTIC
	SOLUTIONS; PRIOR INFORMATION; ELECTRODE ARRAY; ELEMENT-METHOD; HUMAN
	HEAD; ALGORITHMS; DESIGN; BREAST}
}

@ARTICLE{bennett2004,
  author = {Bennett, M. A. and Williams, R. A.},
  title = {Monitoring the operation of an oil/water separator using impedance
	tomography},
  journal = {Minerals Engineering},
  year = {2004},
  volume = {17},
  pages = {605-614},
  number = {5},
  note = {Hydrocyclones 2003 Meeting SEP, 2003 Cape Town, South Africa},
  abstract = {The development and application of an industrial deoiling hydrocyclone
	equipped with electrical resistance tomographic instrumentation is
	described. The use of electrical sensors for continuous monitoring
	of separator operation is. demonstrated. Results show that electrical
	resistance tomography (ERT) is an effective tool for optimising start-up
	and operation of the separator. Subtleties of flow within the hydrocyclone
	can also be sensed, highlighting its potential for use as a validation
	tool for computational fluid dynamics and design models. (C) 2004
	Elsevier Ltd. All rights reserved.}
}

@ARTICLE{borcea2002,
  author = {Borcea, L.},
  title = {Electrical impedance tomography},
  journal = {Inverse Problems},
  year = {2002},
  volume = {18},
  pages = {R99-R136},
  number = {6},
  abstract = {We review theoretical and numerical studies of the inverse problem
	of electrical impedance tomography which seeks the electrical conductivity
	and permittivity inside a body, given simultaneous measurements of
	electrical currents and potentials at the boundary.}
}

@ARTICLE{borsic2001,
  author = {Borsic, A. and McLeod, C. and Lionheart, W. and Kerrouche, N.},
  title = {Realistic 2D human thorax modelling for EIT},
  journal = {Physiological Measurement},
  year = {2001},
  volume = {22},
  pages = {77-83},
  number = {1}
}

@ARTICLE{boverman2008,
  author = {Boverman, G. and Kao, T. J. and Kulkarni, R. and Kim, B. S. and Isaacson,
	D. and Saulnier, G. J. and Newell, J. C.},
  title = {Robust linearized image reconstruction for multifrequency EIT of
	the breast},
  journal = {IEEE Transactions on Medical Imaging},
  year = {2008},
  volume = {27},
  pages = {1439-1448},
  number = {10},
  abstract = {Electrical impedance tomography (EIT) is a developing imaging modality
	that is beginning to show promise for detecting and characterizing
	tumors in the breast. At Rensselaer Polytechnic Institute, we have
	developed a combined EIT-tomosynthesis system that allows for the
	coregistered and simultaneous analysis of the breast using EIT and
	X-ray imaging. A significant challenge in EIT is the design of computationally
	efficient image reconstruction algorithms which are robust to various
	forms of model mismatch. Specifically, we have implemented a scaling
	procedure that is robust to the presence of a thin highly-resistive
	layer of skin at the boundary of the breast and we have developed
	an algorithm to detect and exclude from the image reconstruction
	electrodes that are in poor contact with the breast. In our initial
	clinical studies, it has been difficult to ensure that all electrodes
	make adequate contact with the breast, and thus procedures for the
	use of data sets containing poorly contacting electrodes are particularly
	important. We also present a novel, efficient method to compute the
	Jacobian matrix for our linearized image reconstruction algorithm
	by reducing the computation of the sensitivity for each voxel to
	a quadratic form. Initial clinical results are presented, showing
	the potential of our algorithms to detect and localize breast tumors.}
}

@ARTICLE{brown1994,
  author = {Brown, B. H. and Barber, D. C. and Morice, A. H. and Leathard, A.
	D.},
  title = {Cardiac and respiratory-related electrical-impedance changes in the
	human thorax},
  journal = {IEEE Transactions on Biomedical Engineering},
  year = {1994},
  volume = {41},
  pages = {729-734},
  number = {8},
  abstract = {Electrical impedance measurements have been made from the human trunk
	over the frequency range 9.6 kHz to 614 kHz. Measurements have been
	made from 12 normal subjects and the amplitude of the impedance changes
	associated with the cardiac and respiratory cycles have been recorded.
	It was found that the real part of the impedance fell to 64.0% of
	its low frequency value over the measured range of frequencies and
	that the changes associated with respiration fell in a similar manner.
	However, the cardiac related changes fell more rapidly with increasing
	frequency to 28.2% of the low frequency value. The origin of the
	measured changes is discussed with a view to understanding why the
	cardiac related changes fall more rapidly. It is not possible to
	relate in any simple way the frequency dispersion of a single component
	to that of the whole trunk. However, the results are consistent with
	the lungs being the major origin of both the cardiac and respiratory
	related components. The origin of the cardiac related impedance changes
	could be the pulsatile volume changes in the pulmonary tree. These
	could be shunted by nonpulsatile lung tissue that has decreasing
	impedance at high frequency and thus decreases the relative magnitude
	of the cardiac related changes. This hypothesis needs to be tested
	using localized measurements from the thorax and 3-D modeling of
	the trunk.}
}

@ARTICLE{brown1985,
  author = {Brown, B. H. and Barber, D. C. and Seagar, A. D.},
  title = {Applied potential tomography - possible clinical applications},
  journal = {Clinical Physics and Physiological Measurement},
  year = {1985},
  volume = {6},
  pages = {109-121},
  number = {2}
}

@ARTICLE{brown1987,
  author = {Brown, B H and Seagar, A D},
  title = {The Sheffield data collection system},
  journal = {Clinical Physics and Physiological Measurement},
  year = {1987},
  pages = {91},
  number = {4A},
  abstract = {Because of the intrinsically low sensitivity of any surface potential
	measurement to resistivity changes within a volume conductor, any
	data collection system for impedance imaging must be sensitive to
	changes in the peripheral potential profile of the order of 0.1%.
	For example, whilst the resistivity changes associated with lung
	ventilation and the movement of blood during the cardiac cycle range
	from 3 to 100% the changes recorded at the surface are very much
	less than this. The Sheffield data collection system uses 16 electrodes
	which are addressed through 4 multiplexers. Overall system accuracy
	is largely determined by the front-end equivalent circuit which is
	considered in some detail. This equivalent circuit must take into
	account wiring and multiplexer capacitances. A current drive of 5
	mA p-p at 5 kHz is multiplexed to adjacent pairs of electrodes and
	peripheral potential profiles are recorded by serially stepping around
	adjacent electrode pairs. The existing Sheffield system collects
	the 208 data points for one image in 79 ms and offers 10 image data
	sets per second to the microprocessor. For a homogeneous circular
	conductor the ratio of the maximum to minimum signals within each
	peripheral potential profile is 45:1. The temptation to increase
	the number of electrodes in order to improve resolution is great
	and an achievable performance for 128 electrodes is given. However,
	any improvement in spatial resolution can only be made at the expense
	of speed and sensitivity which may well be the more important factors
	in determining the clinical utility of APT.}
}

@MISC{haroldo2008,
  author = {Haroldo Fraga de Campos Velho},
  title = {Introdu��o aos Problemas Inversos: Aplica��es em Pesquisa Espacial},
  year = {2008},
  url = {http://www.lac.inpe.br/~haroldo/CursoPI/Curso_PI_ELAC-2008-2.pdf}
}

@ARTICLE{chaji2008,
  author = {Chaji, K and Bagdouri, M El and Channa, R},
  title = {A 2D domain boundary estimation},
  journal = {Journal of Physics: Conference Series},
  year = {2008},
  pages = {012029},
  abstract = {This paper presents a numerical method for solving a problem usually
	encountered in thermal imaging. The goal is to estimate an interior
	boundary of a material by applying a known heat flux and measuring
	the induced temperature response on its external boundary. The interior
	boundary is assumed to be under a homogeneous Neumann condition.
	This boundary is first parameterized by a finite-term of Fourrier
	series and the corresponding approximate inverse problem is numerically
	optimized using an iterative Newton method. The required gradient
	is established using the domain derivative techniques. The system
	of heat equations is treated using finite element method for space
	and implicit scheme for time. Some numerical tests are provided to
	illustrate the performances of the proposed method.}
}

@ARTICLE{cheney1999,
  author = {Cheney, Margaret and Isaacson, David and Newell, Jonathan C.},
  title = {Electrical Impedance Tomography},
  journal = {SIAM Review},
  year = {1999},
  volume = {41},
  pages = {85-101},
  number = {1},
  abstract = {This paper surveys some of the work our group has done in electrical
	impedance tomography.}
}

@ARTICLE{cheng1990,
  author = {Cheng, K. S. and Simske, S. J. and Isaacson, D. and Newell, J. C.
	and Gisser, D. G.},
  title = {Errors due to measuring voltage on current-carrying electrodes in
	electric current computed tomography},
  journal = {Biomedical Engineering, IEEE Transactions on},
  year = {1990},
  volume = {37},
  pages = {60-65},
  number = {1},
  keywords = {bioelectric phenomena computerised tomography electric current measurement
	electric impedance electrodes electron device noise measurement errors
	skin voltage measurement body's interior body's surface current carrying
	electrodes current-carrying electrodes electric current computed
	tomography electric-current multiple electrode systems noise levels
	noncurrent-carrying electrodes reconstructed data resistivity signal-to-noise
	ratio skin impedance voltage data}
}

@ARTICLE{cherepenin2002,
  author = {Cherepenin, V. and Karpov, A. and Korjenevsky, A. and Kornienko,
	V. and Kultiasov, Y. and Mazaletskaya, A. and Mazourov, D.},
  title = {Preliminary static EIT images of the thorax in health and disease},
  journal = {Physiological Measurement},
  year = {2002},
  volume = {23},
  pages = {33-41},
  number = {1},
  abstract = {The results of a preliminary clinical evaluation of a one-frequency
	electrical impedance tomography (EIT) system enabling static in vivo
	imaging are presented. The design of the measuring system and image
	reconstruction software are described. Thirty-one subjects were examined
	and divided into four clinical groups. The first group consisted
	of 22 patients with clinical diagnosis of lung cancer with tumour
	localization in one lung. The second group consisted of seven healthy
	subjects. A patient after a one-sided pneumectomy and another with
	one-sided emphysema diagnosis were also examined. Static EIT images
	of a healthy human chest and a chest with various abnormalities are
	given and discussed. The evaluated system distinguishably visualizes
	various states of lungs and thorax including lung cancer. The average
	static conductivity of an affected lung in the first clinical group
	statistically differs from the average conductivity of a healthy
	lung. In spite of low spatial resolution, according to preliminary
	results, the method can be sensitive to cancer and other lung diseases
	in screening investigations.}
}

@ARTICLE{choi2007,
  author = {Choi, M. H. and Kao, T. J. and Isaacson, D. and Saulnier, G. J. and
	Newell, J. C.},
  title = {A reconstruction algorithm for breast cancer imaging with electrical
	impedance tomography in mammography geometry},
  journal = {IEEE Transactions on Biomedical Engineering},
  year = {2007},
  volume = {54},
  pages = {700-710},
  number = {4},
  abstract = {The conductivity and permittivity of breast tumors are known to differ
	significantly from those of normal breast tissues, and electrical
	impedance tomography (EIT) is being studied as a modality for breast
	cancer imaging to exploit these differences. At present, X-ray mammography
	is the primary standard imaging modality used for breast cancer screening
	in clinical practice, so it is desirable to study EIT in the geometry
	of mammography. This paper presents a forward model of a simplified
	mammography geometry and a reconstruction algorithm for breast tumor
	imaging using EIT techniques. The mammography geometry is modeled
	as a rectangular box with electrode arrays on the top and bottom
	planes. A forward model for the electrical impedance imaging problem
	is derived for a homogeneous conductivity distribution and is validated
	by experiment using a phantom tank. A reconstruction algorithm for
	breast tumor imaging based on a linearization approach and the proposed
	forward model is presented. It is found that the proposed reconstruction
	algorithm performs well in the phantom experiment, and that the locations
	of a 5-mm-cube metal target and a 6-mm-cube agar target could be
	recovered at a target depth of 15 mm using a 32 electrode system.}
}

@ARTICLE{brown1989,
  author = {Eyuboglu, B. M. and Brown, B. H. and Barber, D. C.},
  title = {In vivo imaging of cardiac related impedance changes},
  journal = {Engineering in Medicine and Biology Magazine, {IEEE}},
  year = {1989},
  volume = {8},
  pages = {39-45},
  number = {1},
  keywords = {bioelectric phenomena biomedical measurement cardiology computerised
	tomography electric impedance measurement electrocardiography blood
	flow blood perfusion body cardiac activity cardiac output cardiogenic
	electrical resistivity electrical impedance tomography electrical
	resistivity distribution electrodes in vivo imaging lungs pulmonary
	embolism pulmonary perfusion ventricles}
}

@ARTICLE{faes1999,
  author = {Faes, T. J. C. and van der Meij, H. A. and de Munck, J. C. and Heethaar,
	R. M.},
  title = {The electric resistivity of human tissues (100 Hz-10 MHz): a meta-analysis
	of review studies},
  journal = {Physiological Measurement},
  year = {1999},
  volume = {20},
  pages = {R1-R10},
  number = {4},
  abstract = {The electric resistivity of various human tissues has been reported
	in many studies, but on comparison large differences appear between
	these studies. The aim of this study was to investigate systematically
	the resistivities of human tissues as published in review studies
	(100 Hz-10 MHz). A data set of 103 resistivities for 21 different
	human tissues was compiled from six review studies. For each kind
	of tissue the mean and its 95% confidence interval were calculated.
	Moreover, an analysis of covariance showed that the calculated means
	were not statistically different for most tissues, namely skeletal(171
	Omega cm) and cardiac (175 Omega cm) muscle, kidney (211 Omega cm),
	liver (342 Omega cm),lung (157 Omega cm) and spleen (405 Omega cm),
	with bone (>17 583 Omega cm), fat (3850 Omega cm) and, most likely,
	the stratum corneum of the skin having higher resistivities. The
	insignificance of differences between various tissue means could
	imply an equality of their resistivities, or, alternatively, could
	be the result of the large confidence intervals which obscured real
	existing differences. In either case, however, the large 95% confidence
	intervals reflected large uncertainties in our knowledge of resistivities
	of human tissues. Applications based on these resistivities in bioimpedance
	methods, EEG and EKG, should be developed and evaluated with these
	uncertainties in mind.}
}

@ARTICLE{frerichs2000,
  author = {Frerichs, I.},
  title = {Electrical impedance tomography (EIT) in applications related to
	lung and ventilation: a review of experimental and clinical activities},
  journal = {Physiological Measurement},
  year = {2000},
  volume = {21},
  pages = {R1-R21},
  number = {2}
}

@ARTICLE{boxmuller1958,
  author = {George and Muller, Mervin E.},
  title = {A note on the generation of random normal deviates},
  journal = {Ann. Math. Stat.},
  year = {1958},
  volume = {29},
  pages = {610--611},
  number = {2},
  citeulike-article-id = {4096969},
  keywords = {doctoral-thesis},
  posted-at = {2009-02-25 08:34:04},
  priority = {2}
}

@ARTICLE{george2001,
  author = {George, D. L. and Shollenberger, K. A. and Torczynski, J. R. and
	O'Hern, T. J. and Ceccio, S. L.},
  title = {Three-phase material distribution measurements in a vertical flow
	using gamma-densitometry tomography and electrical-impedance tomography},
  journal = {International Journal of Multiphase Flow},
  year = {2001},
  volume = {27},
  pages = {1903-1930},
  number = {11},
  keywords = {Gamma-densitometry tomography Electrical-impedance tomography Bubble
	column Gas volume fraction Multiphase flow}
}

@ARTICLE{george2000,
  author = {George, D. L. and Torczynski, J. R. and Shollenberger, K. A. and
	O'Hern, T. J. and Ceccio, S. L.},
  title = {Validation of electrical-impedance tomography for measurements of
	material distribution in two-phase flows},
  journal = {International Journal of Multiphase Flow},
  year = {2000},
  volume = {26},
  pages = {549-581},
  number = {4},
  keywords = {Electrical-impedance tomography Bubble column Gas volume fraction
	Multiphase flow}
}

@ARTICLE{gisser1987,
  author = {Gisser, D G and Isaacson, D and Newell, J C},
  title = {Current topics in impedance imaging},
  journal = {Clinical Physics and Physiological Measurement},
  year = {1987},
  pages = {39},
  number = {4A},
  abstract = {The authors introduce a definition of 'best' currents to apply to
	an electrode array on the surface of a body in order to distinguish
	between the conductivity inside the body and a conjectured conductivity.
	Using these 'best' currents, they illustrate with a simple example
	the general fact that a single current applied between a pair of
	electrodes loses its ability to distinguish between different conductivities
	as the size of the region over which the current is applied goes
	to zero. They next introduce approximations to the best currents
	on systems having L electrodes, and calculate the ability of these
	systems to distinguish between conductivities as L goes to infinity
	and the electrode size goes to zero. It is concluded with a simple
	example that illustrates a process for producing the 'best' currents
	without a previous knowledge of what is inside the body.}
}

@ARTICLE{hanke2003,
  author = {Hanke, M. and Bruhl, M.},
  title = {Recent progress in electrical impedance tomography},
  journal = {Inverse Problems},
  year = {2003},
  volume = {19},
  pages = {S65-S90},
  number = {6},
  abstract = {We consider the inverse problem of finding cavities within some body
	from electrostatic measurements on the boundary. By a cavity we understand
	any object with a different electrical conductivity from the background
	material of the body. We survey two algorithms for solving this inverse
	problem, namely the factorization method and a MUSIC-type algorithm.
	In particular, we present a number of numerical results to highlight
	the potential and the limitations of these two methods.}
}

@ARTICLE{heikkinen2001,
  author = {Heikkinen, L. M. and Vauhkonen, M. and Savolainen, T. and Leinonen,
	K. and Kaipio, J. P.},
  title = {Electrical process tomography with known internal structures and
	resistivities},
  journal = {Inverse Problems in Engineering},
  year = {2001},
  volume = {9},
  pages = {431-454},
  number = {5}
}

@ARTICLE{holder2005,
  author = {{Holder}, D.S.},
  title = {{Electrical Impedance Tomography: Methods, History and Applications}},
  journal = {Medical Physics},
  year = {2005},
  volume = {32},
  pages = {2731},
  adsnote = {Provided by the SAO/NASA Astrophysics Data System},
  adsurl = {http://adsabs.harvard.edu/abs/2005MedPh..32.2731H},
  doi = {10.1118/1.1995712}
}

@ARTICLE{hou2009,
  author = {Hou, T. C. and Lynch, J. P.},
  title = {Electrical Impedance Tomographic Methods for Sensing Strain Fields
	and Crack Damage in Cementitious Structures},
  journal = {Journal of Intelligent Material Systems and Structures},
  year = {2009},
  volume = {20},
  pages = {1363-1379},
  number = {11},
  abstract = {Cement-based composites (for example, concrete) are brittle materials
	that crack when loaded in tension. Current strategies for crack detection
	are primarily based upon visual inspection by an inspector; such
	approaches are labor-intensive and expensive. Direly needed are sensors
	that can be included within a structural health monitoring (SHM)
	system for automated quantification of crack damage. This study explores
	the use of cementitious materials as their own sensor platform capable
	of measuring mechanical behavior under loading. Fundamentally, this
	self-sensing functionality will be based upon electro-mechanical
	properties. First, the piezoresistivity of cementitious composites
	is quantified so as to establish the material as a multifunctional
	system capable of self-sensing. Second, electrical impedance tomography
	(EIT) is proposed for measuring internal strain fields using only
	electrical measurements taken along the boundary of the structural
	element. An inherent advantage of EIT is that it is a distributed
	sensing approach offering measurement of strain fields across 2D
	or 3D. Furthermore, the approach is well suited for imaging cracks
	which appear as conductivity reductions in EIT-derived conductivity
	maps. Finally, to validate the accuracy of the EIT technique, it
	is applied to fiber reinforced cementitious composite elements loaded
	by axial tension-compression cycles and 3-point bending.}
}

@ARTICLE{hsiao2001,
  author = {Hsiao, Chao-Tsung and Chahine, Georges and Gumerov, Nail},
  title = {Application of a hybrid genetic/powell algorithm and a boundary element
	method to electrical impedance tomography},
  journal = {J. Comput. Phys.},
  year = {2001},
  volume = {173},
  pages = {433-454},
  number = {2}
}

@ARTICLE{Hsiao2001,
  author = {Chao-Tsung Hsiao and Georges Chahine and Nail Gumerov},
  title = {Application of a Hybrid Genetic/Powell Algorithm and a Boundary Element
	Method to Electrical Impedance Tomography},
  journal = {Journal of Computational Physics},
  year = {2001},
  volume = {173},
  pages = {433 - 454},
  number = {2},
  doi = {DOI: 10.1006/jcph.2001.6866},
  issn = {0021-9991},
  url = {http://www.sciencedirect.com/science/article/B6WHY-45BC24W-1K/2/573b38f1f52b58ecdb571950b00e136d}
}

@ARTICLE{kaipio2008,
  author = {Kaipio, Jari},
  title = {Modeling of uncertainties in statistical inverse problems},
  journal = {Journal of Physics: Conference Series},
  year = {2008},
  pages = {012107},
  abstract = {In all real world problems, the models that tie the measurements to
	the unknowns of interest, are at best only approximations for reality.
	While moderate modeling and approximation errors can be tolerated
	with stable problems, inverse problems are a notorious exception.
	Typical modeling errors include inaccurate geometry, unknown boundary
	and initial data, properties of noise and other disturbances, and
	simply the numerical approximations of the physical models. In principle,
	the Bayesian approach to inverse problems, in which all uncertainties
	are modeled as random variables, is capable of handling these uncertainties.
	Depending on the type of uncertainties, however, different strategies
	may be adopted. In this paper we give an overview of typical modeling
	errors and related strategies within the Bayesian framework.}
}

@ARTICLE{karhunen2009,
  author = {Karhunen, Kimmo and Seppanen, Aku and Lehikoinen, Anssi and Monteiro,
	Paulo J. M. and Kaipio, Jari P.},
  title = {Electrical Resistance Tomography imaging of concrete},
  journal = {Cement and Concrete Research},
  year = {2009},
  volume = {40},
  pages = {137-145},
  number = {1},
  keywords = {Concrete (E) Electrical properties (C) Crack detection (B) Non-destructive
	testing}
}

@ARTICLE{kauppinen2006,
  author = {Kauppinen, P and Hyttinen, J and Malmivuo, J},
  title = {Sensitivity distribution visualizations of impedance tomography measurement
	strategies},
  journal = {Int. J. Bioelectromagnetism},
  year = {2006}
}

@ARTICLE{leathard1994,
  author = {Leathard, A. D. and Brown, B. H. and Campbell, J. and Zhang, F. and
	Morice, A. H. and Tayler, D.},
  title = {A comparison of ventilatory and cardiac-related changes in EIT images
	of normal human lungs and of lungs with pulmonary emboli},
  journal = {Physiological Measurement},
  year = {1994},
  volume = {15},
  pages = {A137-A146},
  note = {2A}
}

@BOOK{SNRref,
  title = {Communication Networks: Fundamental Concepts and Key Architectures},
  publisher = {McGraw-Hill, Inc.},
  year = {2003},
  author = {Leon-Garcia, Alberto and Widjaja, Indra},
  address = {New York, NY, USA},
  isbn = {0071198482}
}

@ARTICLE{ma2001,
  author = {Ma, Y. X. and Zheng, S. C. and Xu, L. A. and Liu, X. P. and Wu, Y.
	X.},
  title = {Application of electrical resistance tomography system to monitor
	gas/liquid two-phase flow in a horizontal pipe},
  journal = {Flow Measurement and Instrumentation},
  year = {2001},
  volume = {12},
  pages = {259-265},
  number = {4},
  abstract = {The Electrical Resistance Tomography (ERT) technique possesses great
	potential in monitoring widely exiting industrial two/multi-phase
	flow. For vertical pipe flow and inclined pipe flow, some application
	studies with exciting results have been reported, but there is rarely
	a paper regarding the application of ERT to horizontal gas/liquid
	pipe flow. This paper addresses this issue and proposes a smart method,
	Liquid Level Detection method, to conventional ERT system. The enhanced
	ERT system using the new method can monitor horizontal pipe flow
	effectively and its application is no longer restricted by the flow
	conditions. Some experimental results from monitoring an air/water
	slug pipe flow are presented. (C) 2001 Elsevier Science Ltd. All
	rights reserved.}
}

@BOOK{malmivuo1995,
  title = {Bioelectromagnetism: Principles and Applications of Bioelectric and
	Biomagnetic Fields},
  publisher = {Oxford University Press},
  year = {1995},
  author = {Jaakko Malmivuo and Robert Plonsey}
}

@ARTICLE{mello2008,
  author = {Mello, L. A. M. and de Lima, C. R. and Amato, M. B. P. and Lima,
	R. G. and Silva, E. C. N.},
  title = {Three-Dimensional Electrical Impedance Tomography: A Topology Optimization
	Approach},
  journal = {Biomedical Engineering, IEEE Transactions on},
  year = {2008},
  volume = {55},
  pages = {531-540},
  number = {2},
  abstract = {Electrical impedance tomography is a technique to estimate the impedance
	distribution within a domain, based on measurements on its boundary.
	In other words, given the mathematical model of the domain, its geometry
	and boundary conditions, a nonlinear inverse problem of estimating
	the electric impedance distribution can be solved. Several impedance
	estimation algorithms have been proposed to solve this problem. In
	this paper, we present a three-dimensional algorithm, based on the
	topology optimization method, as an alternative. A sequence of linear
	programming problems, allowing for constraints, is solved utilizing
	this method. In each iteration, the finite element method provides
	the electric potential field within the model of the domain. An electrode
	model is also proposed (thus, increasing the accuracy of the finite
	element results). The algorithm is tested using numerically simulated
	data and also experimental data, and absolute resistivity values
	are obtained. These results, corresponding to phantoms with two different
	conductive materials, exhibit relatively well-defined boundaries
	between them, and show that this is a practical and potentially useful
	technique to be applied to monitor lung aeration, including the possibility
	of imaging a pneumothorax.},
  keywords = {bioelectric phenomena biomedical imaging electric impedance imaging
	finite element analysis inverse problems linear programming lung
	pneumodynamics tomography 3D electrical impedance tomography electric
	impedance distribution electric potential field finite element method
	lung aeration nonlinear inverse problem pneumothorax imaging topology
	optimization approach Electrode model medical imaging three-dimensional
	electrical impedance tomography topology optimization}
}

@ARTICLE{mera2007,
  author = {Mera, N. S.},
  title = {Efficient optimization processes using kriging approximation models
	in electrical impedance tomography},
  journal = {International Journal for Numerical Methods in Engineering},
  year = {2007},
  volume = {69},
  pages = {202-220},
  number = {1}
}

@ARTICLE{park2008,
  author = {Park, B. G. and Moon, J. H. and Lee, B. S. and Kim, S.},
  title = {An electrical resistance tomography technique for the monitoring
	of a radioactive waste separation process},
  journal = {International Communications in Heat and Mass Transfer},
  year = {2008},
  volume = {35},
  pages = {1307-1310},
  number = {10},
  abstract = {An electrical resistance tomography (ERT) technique is suggested to
	monitor a radioactive waste separation process. This paper presents
	analytical results for a simple model problem to estimate the boundary
	between two distinct waste streams in a rotating separator as well
	as the conductivity value of each stream. To solve this highly non-linear
	identification problem, the particle swarm optimization (PSO) algorithm
	is successfully introduced. The results show the feasibility of the
	ERT for monitoring the separation process. (c) 2008 Elsevier Ltd.
	All rights reserved.}
}

@MISC{patterson2005,
  author = {R. Patterson and Fei Yang},
  title = {Lung Impedance Contributions to the Total Impedance based on a FDM
	Model and Lead Field Theory},
  year = {2005}
}

@ARTICLE{patterson2003,
  author = {Patterson, R. P. and Zhang, J.},
  title = {Evaluation of an EIT reconstruction algorithm using finite difference
	human thorax models as phantoms},
  journal = {Physiological Measurement},
  year = {2003},
  volume = {24},
  pages = {467-475},
  number = {2}
}

@ARTICLE{pullan2001,
  author = {Pullan, A. J. and Cheng, L. K. and Nash, M. P. and Bradley, C. P.
	and Paterson, D. J.},
  title = {Noninvasive Electrical Imaging of the Heart: Theory and Model Development},
  journal = {Annals of Biomedical Engineering},
  year = {2001},
  volume = {29},
  pages = {817-836},
  number = {10},
  abstract = {The aim of this work is to begin quantifying the performance of a
	recently developed activation imaging algorithm of Huiskamp and Greensite
	[IEEE Trans. Biomed. Eng. 44:433–446]. We present here the modeling
	and computational issues associated with this process. First, we
	present a practical construction of the appropriate transfer matrix
	relating an activation sequence to body surface potentials from a
	general boundary value problem point of view. This approach makes
	explicit the role of different Green's functions and elucidates features
	(such as the anisotropic versus isotropic distinction) not readily
	apparent from alternative formulations. A new analytic solution is
	then developed to test the numerical implementation associated with
	the transfer matrix formulation presented here and convergence results
	for both potentials and normal currents are given. Next, details
	of the construction of a generic porcine model using a nontraditional
	data-fitting procedure are presented. The computational performance
	of this model is carefully examined to obtain a mesh of an appropriate
	resolution to use in inverse calculations. Finally, as a test of
	the entire approach, we illustrate the activation inverse procedure
	by reconstructing a known activation sequence from simulated data.
	For the example presented, which involved two ectopic focii with
	large amounts of Gaussian noise (100 µV rms) present in the torso
	signals, the reconstructed activation sequence had a similarity index
	of 0.880 when compared to the input source. © 2001 Biomedical Engineering
	Society.}
}

@MISC{patterson2001,
  author = {RP Patterson, J Zhang, LI Mason, M Jerosch-Herold},
  title = {Variability in the cardiac EIT image as a function of electrode position,
	lung volume and body position.},
  year = {2001}
}

@ARTICLE{soni2006,
  author = {Soni, N. K. and Paulsen, K. D. and Dehghani, H. and Hartov, A.},
  title = {Finite element implementation of Maxwell's equations for image reconstruction
	in electrical impedance tomography},
  journal = {IEEE Transactions on Medical Imaging},
  year = {2006},
  volume = {25},
  pages = {55-61},
  number = {1},
  abstract = {Traditionally, image reconstruction in electrical impedance tomography
	(EIT) has been based on Laplace's equation. However, at high frequencies
	the coupling between electric and magnetic fields requires solution
	of the full Maxwell equations. In this paper, a formulation is presented
	in terms of the Maxwell equations expressed in scalar and vector
	potentials. The approach leads to boundary conditions that naturally
	align with the quantities measured by EIT instrumentation. A two-dimensional
	implementation for image reconstruction from EIT data is realized.
	The effect of frequency on the field distribution is illustrated
	using the high-frequency model and is compared with Laplace solutions.
	Numerical simulations and experimental results are also presented
	to illustrate image reconstruction over a range of frequencies using
	the new implementation. The results show that scalar/vector potential
	reconstruction produces images which are essentially indistinguishable
	from a Laplace algorithm for frequencies below 1 MHz but superior
	at frequencies reaching 10 MHz.},
  keywords = {(A, Phi) formulation; electrical impedance tomography; finite element
	method; high-frequency EIT; inverse problems; Maxwell's equations
	VECTOR PARASITES; TISSUE}
}

@ARTICLE{stephenson2008,
  author = {Stephenson, D R and Mann, R and York, T A},
  title = {The sensitivity of reconstructed images and process engineering metrics
	to key choices in practical electrical impedance tomography},
  journal = {Measurement Science and Technology},
  year = {2008},
  pages = {094013},
  number = {9},
  abstract = {This paper explores, from an experimental perspective, the dramatic
	effect that measurement strategy, reconstruction algorithm and reconstruction
	parameters can have on electrical impedance tomography images. Measurement
	data, from a stirred tank and jet mixer, have been acquired using
	two tomographs from the University of Cape Town and Industrial Tomography
	Systems Ltd respectively. Simulations consider conductively contrasting
	objects that are placed strategically in the vessel. The adjacent
	and opposite measurement strategies are employed to interrogate an
	unbaffled mixing tank. The superior sensitivity of the opposite strategy
	in the centre of the vessel is verified. For a central inclusion,
	simulated results suggest 4% 'image error' compared to 6% for the
	adjacent strategy. Five reconstruction algorithms: Linear Back Projection,
	Landweber, Conjugate Gradients, Generalized Singular Value Decomposition
	(GSVD) and Nonlinear Gauss Newton, have been considered. A measure
	of 'image error' is typically below 10%, but values as high as 30%
	are not unusual with algorithms such as Linear Back Projection. For
	a homogeneous step change in conductivity 'image error' is seen to
	vary from 3% for Nonlinear Gauss Newton to 150% for Linear Back Projection.
	Corresponding measures of the coefficient of variation range from
	25% to 44%. Overall it is suggested that the GSVD algorithm provides
	the best balance of attributes for identifying discrete objects and
	for homogeneous step changes. The dramatic effect of regularization
	parameters is illustrated by considering the GSVD. The use of the
	discrete Picard condition to determine optimum values is demonstrated.
	Mixing lengths have been calculated from the reconstructed image
	data and this is seen to vary dramatically with the regularization
	parameter.}
}

@ARTICLE{tortora2006,
  author = {Tortora, P. R. and Ceccio, S. L. and O'Hern, T. J. and Trujillo,
	S. M. and Torczynski, J. R.},
  title = {Quantitative measurement of solids distribution in gas-solid riser
	flows using electrical impedance tomography and gamma densitometry
	tomography},
  journal = {International Journal of Multiphase Flow},
  year = {2006},
  volume = {32},
  pages = {972-995},
  number = {8},
  keywords = {EIT GDT Tomography Fluidized bed Riser Gas-solid}
}

@ARTICLE{vauhkonen1997,
  author = {M Vauhkonen and J P Kaipio and E Somersalo and P A Karjalainen},
  title = {Electrical impedance tomography with basis constraints},
  journal = {Inverse Problems},
  year = {1997},
  volume = {13},
  pages = {523-530},
  number = {2},
  abstract = {In this paper, we consider the impedance tomography problem of estimating
	the conductivity distribution within the body from static current/voltage
	measurements on the body's surface. We present a new method of implementing
	prior information of the conductivities in the optimization algorithm.
	The method is based on the approximation of the prior covariance
	matrix by simulated samples of feasible conductivities. The reduction
	of the dimensionality of the optimization problem is performed by
	principal component analysis (PCA).},
  url = {http://stacks.iop.org/0266-5611/13/523}
}

@ARTICLE{vilar2008,
  author = {Vilar, G. and Williams, R. A. and Wang, M. and Tweedie, R. J.},
  title = {On line analysis of structure of dispersions in an oscillatory baffled
	reactor using electrical impedance tomography},
  journal = {Chemical Engineering Journal},
  year = {2008},
  volume = {141},
  pages = {58-66},
  number = {1-3},
  keywords = {Online analysis Tomography sensor Oscillatory baffled reactor}
}

@ARTICLE{wang2005,
  author = {Wang, M.},
  title = {Impedance mapping of particulate multiphase flows},
  journal = {Flow Measurement and Instrumentation},
  year = {2005},
  volume = {16},
  pages = {183-189},
  number = {2-3},
  keywords = {Electrical resistance tomography Multi-DSP Sensor Mixing Flows Bubble
	column}
}

@ARTICLE{watzenig2008,
  author = {Watzenig, Daniel and Fox, Colin},
  title = {Posterior variability of inclusion shape based on tomographic measurement
	data},
  journal = {Journal of Physics: Conference Series},
  year = {2008},
  pages = {012102},
  abstract = {We treat the problem of recovering the unknown shape of a single inclusion
	with unknown constant permittivity in an otherwise uniform background
	material, from uncertain measurements of trans-capacitance at electrodes
	outside the material. The ubiquitous presence of measurement noise
	implies that the practical measurement process is probabilistic,
	and the inverse problem is naturally stated as statistical inference.
	Formulating the inverse problem in a Bayesian inferential framework
	requires accurately modelling the forward map, measurement noise,
	and specifying a prior distribution for the cross-sectional material
	distribution. Numerical implementation of the forward map is via
	the boundary element method (BEM) taking advantage of a piecewise
	constant representation. Summary statistics are calculated using
	MCMC sampling to characterize posterior variability for synthetic
	and measured data sets.}
}

@INCOLLECTION{you2009,
  author = {You, Fusheng and Shuai, Wanjun and Shi, Xuetao and Fu, Feng and Liu,
	Ruigang and Dong, Xiuzhen},
  title = {In vivo Monitoring by EIT for the Pig's Bleeding after Liver Injury},
  year = {2009},
  pages = {110-112},
  abstract = {Many reasons, such as traffic accident, abdomen post-operation, etc.,
	may cause intraperitoneal bleeding. To further demonstrate the feasibility
	of non-invasive monitoring of EIT for intraperitoneal bleeding, pig's
	bleeding model of liver injury was made. The pig's liver was hurt
	by puncture needle manually so that the internal autobleeding process
	is continuous and nature, which resembles the clinical bleeding process
	of abdominal organ injuries. Totally 5 cases of 3 month old pig's
	bleeding of liver injury were monitored by EIT. In the experiments,
	16 electrodes were placed around the skin-prepared abdomen, an alternating
	current (1mA, 50KHz) was applied on polar driven pattern, and the
	improved back-projection algorithm was used for image reconstruction.
	The EIT system imaged at 1 frame per second. The monitor time lasted
	about 40~120 minutes till the subject was dying or dead of hemorrhoea.
	After paunching each pig, the total bleeding volume was measured
	and it ranged from 450~870ml. The imaging results show that after
	liver injury, the bleeding area in EIT images become redder and larger
	gradually with the bleeding process going on, indicating EIT could
	monitor the development of the pig's liver bleeding dynamically and
	noninvasively.}
}

@MISC{zhang2004,
  author = {J. Zhang and R.P. Patterson},
  title = {Analysis on the influence of tissues/organs' movements in EIT images
	of lung ventilation using finite difference thorax models},
  year = {2004}
}

@INPROCEEDINGS{zlochiver2006,
  author = {Zlochiver, S. and Freimark, D. and Arad, M. and Adunsky, A. and Abboud,
	S.},
  title = {Parametric EIT for monitoring cardiac stroke volume},
  year = {2006},
  volume = {27},
  pages = {S139-S146},
  publisher = {Iop Publishing Ltd},
  abstract = {The bio-impedance technique appears appropriate for non-invasive cardiac
	stroke volume (SV) measurement, as the thoracic conductivity distribution
	is altered during the cardiac cycle due to the heart contraction
	and blood perfusion. In the present work, the feasibility of a parametric
	electrical impedance tomography (EIT) for assessing the cardiac SV
	was studied. An impedance model of the thorax was constructed from
	segmented axial MRI images along 19 phases of the cardiac cycle.
	The heart was simulated as an ellipsoid, with its axes' lengths set
	as the reconstruction parameters, while all other tissues' geometry
	and conductivity values were kept fixed. A Newton-Raphson parametric
	optimization scheme was utilized, yielding a correlation between
	the reconstructed and anatomical left ventricular volumes of 0.97
	(P = 2 x 10(-11)). An analysis of noise sensitivity showed that the
	proposed algorithm requires an SNR greater than 65 dB. The simulation
	results were compared to physical data, collected with a portable
	EIT system (PulmoTrace (TM), CardioInspect). The validation study
	was employed for a group of N = 28 healthy patients, and a comparison
	with impedance cardiography measurements (BioZ (R), Cardiodynamics)
	was made, showing a correlation of r = 0.86 (p = 4 x 10(-9)). The
	preliminary results demonstrate that parametric EIT has the potential
	to measure SV, and may be applicable for both clinical and home environment
	usage.},
  keywords = {parametric reconstruction; SV measurement; simulation study; clinical
	trial Biophysics; Engineering, Biomedical; Physiology}
}

@ARTICLE{zou2003,
  author = {Zou, Y. and Guo, Z.},
  title = {A review of electrical impedance techniques for breast cancer detection},
  journal = {Medical Engineering $\&$ Physics},
  year = {2003},
  volume = {25},
  pages = {79-90},
  number = {2},
  abstract = {Some evidence has been found that malignant breast tumors have lower
	electrical impedance than surrounding normal tissues. Although the
	separation of malignant tumors from benign lesions based on impedance
	measurements needs further investigation, electrical impedance could
	be used as an indicator for breast cancer detection. In this paper,
	we provide a systematic technical review of the existing electrical
	impedance techniques proposed for breast cancer detection, with an
	emphasis on noninvasive impedance imaging techniques. The electrical
	impedance of human breast tissue is first introduced, with tabulation
	of previous in vitro impedance measurement results on cancerous and
	normal breast tissues, and a brief description on the limited in
	vivo impedance measurements completed with invasive, or noninvasive,
	non-imaging techniques. A detailed review on noninvasive impedance
	imaging techniques for breast cancer detection, such as electrical
	impedance tomography (EIT) and electrical impedance mapping (EIM),
	is then presented. We suggest that for better breast cancer detection,
	an invasive impedance technique may be enhanced by combination with
	other cancer indicators. 3D EIT should be improved through collective
	efforts. EIM using a pair of electrode arrays is a viable method
	with great potential. Magnetic induction tomography and other magnetic
	induction based impedance imaging for breast cancer detection are
	promising and merit further exploration as well. (C) 2003 IPEM. Published
	by Elsevier Science Ltd. All rights reserved.}
}

